Feature Comparison
| Feature | ticket-rs | Beads | JIRA/Linear | GitHub Issues |
|---|---|---|---|---|
| Git-backed | ✅ Markdown + YAML | ✅ SQLite + git | ❌ Cloud database | ❌ Cloud database |
| Dependencies | ✅ Built-in graph | ✅ Built-in | ⚠️ Limited | ❌ None |
| Graph Analytics | ✅ PageRank, critical path | ⚠️ Basic | ❌ None | ❌ None |
| AI-Native | ✅ MCP, hooks, triage | ✅ Good CLI | ⚠️ API only | ⚠️ API only |
| Offline Mode | ✅ Full functionality | ✅ Full functionality | ❌ Requires network | ❌ Requires network |
| Background Process | ✅ None (stateless) | ❌ SQLite daemon | ❌ Browser required | ❌ Browser required |
| Installation | ✅ Single binary | ⚠️ Go + SQLite | ❌ Browser only | ❌ Browser only |
| External Sync | ✅ GitHub, Linear | ❌ None | N/A (is the system) | N/A (is the system) |
| Sandboxed Env | ✅ Works everywhere | ⚠️ Needs SQLite | ❌ API tokens | ❌ API tokens |
| Merge Conflicts | ✅ Rare (text files) | ❌ SQLite conflicts | N/A | N/A |
| Team UI | ⚠️ CLI + sync | ❌ CLI only | ✅ Rich web UI | ✅ GitHub UI |
| Speed | ✅ Rust performance | ✅ Go performance | ⚠️ Network latency | ⚠️ Network latency |
Performance Benchmarks
We maintain a comprehensive benchmark suite comparing ticket-rs against alternative implementations including bash scripts and Go-based tools (beads). All benchmarks are automated and run with Monte Carlo analysis across multiple dataset sizes.Benchmark Results
Overall Performance (500 tickets, 30 iterations, averaged across all commands):| Implementation | Avg Time | vs Bash | Notes |
|---|---|---|---|
| ticket-py (Python bindings) | 14.1ms | 2.7× faster | In-process Rust via PyO3 |
| tk (Rust CLI) | 21.4ms | 1.8× faster | Single binary, subprocess |
| ticket (Bash baseline) | 38.3ms | 1.0× (baseline) | Pure bash script |
| beads Go direct | 46.6ms | 1.2× slower | JSONL parsing |
| beads Go daemon | 95.6ms | 2.5× slower | SQLite + daemon overhead |
PyO3 Performance
Fastest implementation with zero subprocess overhead. Perfect for Python-first workflows.
Rust CLI Speed
1.8× faster than bash with no dependencies. Single binary, instant startup.
Linear Scaling
O(n) complexity with excellent constants. Handles 1,000+ issues efficiently.
Detailed Command Performance
Operations tested:ready, list, show, stats, create, update
Highlights:
- Ready command: Finds unblocked issues in <7ms (vs 35ms in bash)
- List command: Full issue list in <8ms (vs 17ms in bash)
- Show command: Single issue lookup in <2ms after O(1) optimization
- Triage: AI-optimized report with PageRank in ~12ms
Scaling Analysis
Tested with 10, 50, 100, 500, and 1,000 ticket datasets:- ticket-rs/ticket-py: O(n) scaling with minimal overhead
- bash: O(n²) for operations requiring full repository scans
- beads daemon: Constant daemon overhead + O(n) parsing
View full benchmark methodology, charts, and raw data in
pypi/benchmarks/BENCHMARK_REPORT.mdWhen to Use ticket-rs
ticket-rs is ideal when you:Work primarily in the terminal and IDE
Use AI coding assistants (Claude, Cursor, Windsurf)
Want git-backed issue tracking that versions with code
Need dependency graphs and smart prioritization
Value offline capability and zero external dependencies
Work in sandboxed environments (CI/CD, containers)
Want blazing fast commands (milliseconds, not seconds)
When NOT to Use ticket-rs
Consider alternatives when you:Detailed Comparisons
vs. Beads
Beads pioneered AI-native issue tracking. ticket-rs builds on those ideas:- Similarities
- Differences
- Migration
- ✅ Git-backed storage
- ✅ Dependency tracking
- ✅ AI-native CLI
- ✅ Terminal-first workflow
vs. JIRA / Linear
JIRA and Linear are full-featured project management systems. ticket-rs is developer-focused.- When to Use JIRA/Linear
- When to Use ticket-rs
- Best of Both
- Team needs rich web UI
- Non-technical stakeholders
- Complex workflows (sprints, epics, boards)
- Advanced reporting and dashboards
- Real-time collaboration
vs. GitHub Issues
GitHub Issues is tightly integrated with GitHub. ticket-rs is git-native.- GitHub Issues Pros
- ticket-rs Advantages
- Sync Both
- Built into GitHub (no separate tool)
- Rich web UI
- Integrations with Actions, Projects
- Team-friendly interface
vs. Plain Text / Markdown Files
Some teams just use TODO.md or NOTES.md. ticket-rs adds structure:| Aspect | Plain Files | ticket-rs | Notes |
|---|---|---|---|
| Structure | Freeform | YAML frontmatter | YAML frontmatter is a simple way to add structured data to your issues |
| Dependencies | Manual tracking | Automatic graph | Help your agents traverse a rich context graph |
| Search | grep | tk grep, tk search | Fast term-based and BM25-based search |
| Similarity | None | tk similar | tk similar finds issues similar to a given issue |
| Deduplication | None | tk duplicates | tk duplicates finds and manages duplicate issues |
| Status | Comments | Structured status field | Structured status field is a way to track the status of your issues |
| Analytics | None | PageRank, critical path | PageRank and critical path are ways to analyze your issues |
| AI Integration | Generic | Purpose-built (MCP, hooks) | tk prime outputs AI-optimized workflow context |